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Re: st: r(198) error using lrtest to test for heteroskedasticity.


From   Nick Cox <[email protected]>
To   [email protected]
Subject   Re: st: r(198) error using lrtest to test for heteroskedasticity.
Date   Sat, 7 Jul 2012 01:44:03 +0100

You omitted to estimate the model again. Therefore -hetero- is still
the most recent set of estimates and you are comparing it with itself.
The -lrtest- hinges on comparing two different model fits. If you look
again at the FAQ you will see that there are two model fits.

(I first looked at your bottom line, which looked wrong. I didn't
notice in my first posting that you made two mistakes.)

Nick

On Sat, Jul 7, 2012 at 12:07 AM, Sean Lim <[email protected]> wrote:
> Dear Nick,
>
> Thank you for your reply.
>
> I have tried the commands with the alterations you suggested.
>
> I am afraid I still have the same error even when I include the period(.).
>
> . lrtest hetero . , df(20)
> models hetero specified more than once
> r(198);
>
> Could this be an issue with my dataset? I have a very unbalanced panel
> with many data points missing in the independent variables.
>
> On 6 July 2012 19:24, Nick Cox <[email protected]> wrote:
>> The FAQ recommends different syntax. You omitted the period (.) in
>>
>> lrtest hetero . , df(`df')
>>
>> Nick
>>
>> On Fri, Jul 6, 2012 at 1:15 PM, Sean Lim <[email protected]> wrote:
>>> Dear Statalisters,
>>>
>>> I am trying to test for heteroskedasticity in a panel dataset I have.
>>> I am following the steps described in
>>> http://www.stata.com/support/faqs/statistics/panel-level-heteroskedasticity-and-autocorrelation/
>>>  but I am getting an error: " r(198) error when trying to use lrtest.
>>>
>>>
>>> Any advice on how I should continue with this is appreciated. Below is
>>> my output.
>>>
>>> Many thanks,
>>>
>>>
>>> Sean
>>>
>>> . xtgls leverage avol7 time_tomaturity grade1 bid_ask_predict, igls
>>> panels(heteroskedastic)
>>> Iteration 1: tolerance = .03519474
>>> Iteration 2: tolerance = .10619771
>>> Iteration 3: tolerance = .13432693
>>> Iteration 4: tolerance = .12540942
>>> Iteration 5: tolerance = .0969322
>>> Iteration 6: tolerance = .02952538
>>> Iteration 7: tolerance = .01171261
>>> Iteration 8: tolerance = .00374088
>>> Iteration 9: tolerance = .00121751
>>> Iteration 10: tolerance = .00043942
>>> Iteration 11: tolerance = .00016508
>>> Iteration 12: tolerance = .00006333
>>> Iteration 13: tolerance = .00002464
>>> Iteration 14: tolerance = 9.688e-06
>>> Iteration 15: tolerance = 3.844e-06
>>> Iteration 16: tolerance = 1.537e-06
>>> Iteration 17: tolerance = 6.189e-07
>>> Iteration 18: tolerance = 2.506e-07
>>> Iteration 19: tolerance = 1.019e-07
>>> Iteration 20: tolerance = 4.167e-08
>>>
>>>
>>> Cross-sectional time-series FGLS regression
>>>
>>> Coefficients:  generalized least squares
>>> Panels:        heteroskedastic
>>> Correlation:   no autocorrelation
>>>
>>> Estimated covariances      =        21          Number of obs      =     15018
>>> Estimated autocorrelations =         0          Number of groups   =        21
>>> Estimated coefficients     =         5          Obs per group: min =       110
>>>                                                                avg =  715.1429
>>>                                                                max =       782
>>>                                                 Wald chi2(4)       = 953523.91
>>> Log likelihood             =  13896.44          Prob > chi2        =    0.0000
>>>
>>> ------------------------------------------------------------------------------
>>>     leverage |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
>>> -------------+----------------------------------------------------------------
>>>        avol7 |  -.7824862   .0049243  -158.90   0.000    -.7921376   -.7728347
>>> time_tomat~y |  -.0002712   .0000154   -17.65   0.000    -.0003013   -.0002411
>>>       grade1 |   -.399934   .0010845  -368.76   0.000    -.4020597   -.3978084
>>> bid_ask_p~ct |   .0661513   .0043105    15.35   0.000     .0577029    .0745996
>>>        _cons |   .9815676   .0009443  1039.42   0.000     .9797167    .9834184
>>> ------------------------------------------------------------------------------
>>>
>>> . estimates store hetero
>>>
>>> . local df = e(N_g) - 1
>>>
>>> . di `df'
>>> 20
>>>
>>> . lrtest hetero , df(20)
>>> models hetero specified more than once
>>> r(198);
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